4.7 Article

Intratumoral metabolic heterogeneity predicts invasive components in breast ductal carcinoma in situ

Journal

EUROPEAN RADIOLOGY
Volume 25, Issue 12, Pages 3648-3658

Publisher

SPRINGER
DOI: 10.1007/s00330-015-3761-9

Keywords

DCIS; Invasive carcinoma; Positron emission tomography; Breast-specific gamma imaging; Diffusion magnetic resonance imaging

Funding

  1. National Research Foundation of South Korea [2012R1A1A1012913, 2012M3A9B6055379]
  2. National Research Foundation of Korea [2012M3A9B6055379, 2012R1A1A1012913] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study investigated whether texture-based imaging parameters could identify invasive components of ductal carcinoma in situ (DCIS). We enrolled 65 biopsy-confirmed DCIS patients (62 unilateral, 3 bilateral) who underwent (18) F-FDG PET, diffusion-weighted imaging (DWI), or breast-specific gamma imaging (BSGI). We measured SUV (max) and intratumoral metabolic heterogeneity by the area under the curve (AUC) of cumulative SUV histograms (CSH) on PET, tumour-to-normal ratio (TNR) and coefficient of variation (COV) as an index of heterogeneity on BSGI, minimum ADC (ADC (min) ) and ADC difference (ADC (diff) ) as an index of heterogeneity on DWI. After surgery, final pathology was categorized as pure-DCIS (DCIS-P), DCIS with microinvasion (DCIS-MI), or invasive ductal carcinoma (IDC). Clinicopathologic features of DCIS were correlated with final classification. Final pathology confirmed 44 DCIS-P, 14 DCIS-MI, and 10 IDC. The invasive component of DCIS was significantly correlated with higher SUV (max) (p = 0.017) and lower AUC-CSH (p < 0.001) on PET, higher TNR (p = 0.008) and COV (p = 0.035) on BSGI, lower ADC (min) (p = 0.016) and higher ADC (diff) (p = 0.009) on DWI, and larger pathologic size (p = 0.018). On multiple regression analysis, AUC-CSH was the only significant predictor of invasive components (p = 0.044). The intratumoral metabolic heterogeneity of (18) F-FDG PET was the most important predictor of invasive components of DCIS. aEuro cent Preoperative identification of invasion in DCIS is important for axillary nodal management aEuro cent Higher SUV (max) and lower AUC-CSH from FDG PET may indicate invasive components of DCIS aEuro cent Higher TNR and COV from BSGI may indicate invasive components of DCIS aEuro cent Lower ADC (min) and higher ADC (diff) from DWI may indicate invasive components of DCIS aEuro cent AUC-CSH, an index of metabolic heterogeneity, is an independent predictor for invasive components.

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